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ArcGIS is a family of client, server and online geographic information system (GIS) software developed and maintained by Esri. ArcGIS was first released in 1982 as ARC/INFO, a command line-based GIS. ARC/INFO was later merged into ArcGIS Desktop, which was eventually superseded by ArcGIS Pro in 2015. [8]
GIS-based network analysis may be used to address a wide range of practical problems such as route selection and facility location (core topics in the field of operations research), and problems involving flows such as those found in Hydrospatial and hydrology and transportation research. In many instances location problems relate to networks ...
The core of any GIS is a database that contains representations of geographic phenomena, modeling their geometry (location and shape) and their properties or attributes. A GIS database may be stored in a variety of forms, such as a collection of separate data files or a single spatially-enabled relational database. Collecting and managing these ...
The older ArcGIS Desktop consisted of several integrated applications, including ArcMap, ArcCatalog, ArcToolbox, ArcScene, and ArcGlobe. Esri's main desktop, or thick client, application is ArcGIS Pro which is slowly replacing the former main components of ArcGIS Desktop: ArcMap, ArcCatalog and ArcToolbox. Esri's desktop products allow users to ...
The shapefile format is a geospatial vector data format for geographic information system (GIS) software.It is developed and regulated by Esri as a mostly open specification for data interoperability among Esri and other GIS software products. [1]
The problems of finding a Hamiltonian path and a Hamiltonian cycle can be related as follows: In one direction, the Hamiltonian path problem for graph G can be related to the Hamiltonian cycle problem in a graph H obtained from G by adding a new universal vertex x, connecting x to all vertices of G.
The United States National Grid (USNG) is a multi-purpose location system of grid references used in the United States.It provides a nationally consistent "language of location", optimized for local applications, in a compact, user friendly format.
Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data preprocessing.. The data is linearly transformed onto a new coordinate system such that the directions (principal components) capturing the largest variation in the data can be easily identified.